{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "6bf97523-882f-40a8-93e5-a737b2ebb045",
   "metadata": {},
   "source": [
    "# <span style=\"color: orange\">四  标注柱形图</span>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "82c47ddc-542f-4ebf-8edc-3ed9fa2cf5ff",
   "metadata": {},
   "source": [
    "# 一.筛选数据\n",
    "### 根据ERP订单数据文件的数据，筛选出裙子，毛衣，卫衣，裤子，夹克，外套，T恤，衬衫的订单数量。\n",
    "### <span style=\"color: red\">依旧根据筛选的数据，用python实现标注柱形图</span>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "66cdf32d-7daa-45a8-b6ea-c80e54839005",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========================================\n",
      "ERP订单数据 - 商品类别订单数量统计\n",
      "========================================\n",
      "  裙子: 120 个订单\n",
      "  毛衣: 107 个订单\n",
      "  卫衣: 127 个订单\n",
      "  裤子: 134 个订单\n",
      "  夹克: 126 个订单\n",
      "  外套: 123 个订单\n",
      "  T恤: 134 个订单\n",
      "  衬衫: 129 个订单\n",
      "========================================\n",
      "  总计: 1000 个订单\n",
      "原始数据总订单数: 1000 条\n"
     ]
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "# ---------------------- 1. 数据读取与统计 ----------------------\n",
    "data=pd.read_excel(\"ERP订单数据.xlsx\")\n",
    "\n",
    "target_categories = {\n",
    "    \"裙子\": \"裙子\",\n",
    "    \"毛衣\": \"毛衣\",\n",
    "    \"卫衣\": \"卫衣\",\n",
    "    \"裤子\": \"裤子\",\n",
    "    \"夹克\": \"夹克\",\n",
    "    \"外套\": \"外套\",\n",
    "    \"T恤\": \"T恤\",\n",
    "    \"衬衫\": \"衬衫\"\n",
    "}\n",
    "\n",
    "# 统计各类别订单数量\n",
    "category_counts = {}\n",
    "for category, keyword in target_categories.items():\n",
    "    # 筛选\"商品名称\"中包含对应关键词的订单，统计数量\n",
    "    count = data[data[\"商品名称\"].str.contains(keyword, na=False)].shape[0]\n",
    "    category_counts[category] = count\n",
    "\n",
    "# \n",
    "#打印统计结果（格式化输出，清晰展示）\n",
    "print(\"=\" * 40)\n",
    "print(\"ERP订单数据 - 商品类别订单数量统计\")\n",
    "print(\"=\" * 40)\n",
    "for category, count in category_counts.items():\n",
    "    print(f\"{category:>4}: {count:>3} 个订单\")  # 右对齐，排版更整齐\n",
    "print(\"=\" * 40)\n",
    "# 可选：打印总计（验证统计完整性）\n",
    "total_count = sum(category_counts.values())\n",
    "print(f\"{'总计':>4}: {total_count:>3} 个订单\")\n",
    "print(f\"{'原始数据总订单数':>4}: {data.shape[0]:>3} 条\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "31976867-f452-4a43-8673-a8fe3ce92b3f",
   "metadata": {},
   "source": [
    "# 二.可视化\n",
    "### 使用以上筛选的数据，生成一个标注柱形图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "334f26b6-d314-4133-864d-c93c592ee9bb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1400x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from matplotlib.patches import FancyBboxPatch\n",
    "\n",
    "# 设置中文字体\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei', 'Microsoft YaHei', 'DejaVu Sans']\n",
    "plt.rcParams['axes.unicode_minus'] = False\n",
    "\n",
    "# 创建图形和坐标轴\n",
    "fig, ax = plt.subplots(figsize=(14, 9))\n",
    "\n",
    "# 设置深蓝色背景\n",
    "fig.patch.set_facecolor('#0a1c3d')\n",
    "ax.set_facecolor('#0a1c3d')\n",
    "\n",
    "# 准备数据\n",
    "categories = list(category_counts.keys())\n",
    "counts = list(category_counts.values())\n",
    "\n",
    "# 找出最大和最小销量的商品\n",
    "max_count = max(counts)\n",
    "min_count = min(counts)\n",
    "max_category = categories[counts.index(max_count)]\n",
    "min_category = categories[counts.index(min_count)]\n",
    "\n",
    "# 定义颜色映射（根据化妆品图的颜色）\n",
    "colors_map = {\n",
    "    \"裙子\": \"#ADD8E6\",  # 浅蓝色（口红颜色）\n",
    "    \"毛衣\": \"#90EE90\",  # 浅绿色（面膜颜色）\n",
    "    \"卫衣\": \"#FF4500\",  # 橙红色（隔离颜色）\n",
    "    \"裤子\": \"#FFD700\",  # 黄色（防晒颜色）\n",
    "    \"夹克\": \"#4682B4\",  # 深蓝色（精华颜色）\n",
    "    \"外套\": \"#4682B4\",  # 深蓝色（面霜颜色）\n",
    "    \"T恤\": \"#9370DB\",   # 紫色（眼影颜色）\n",
    "    \"衬衫\": \"#9370DB\"   # 紫色（气垫颜色）\n",
    "}\n",
    "\n",
    "# 创建柱状图\n",
    "x_pos = np.arange(len(categories))\n",
    "bar_width = 0.6\n",
    "\n",
    "# 绘制柱状图\n",
    "bars = ax.bar(x_pos, counts, width=bar_width, color=[colors_map[cat] for cat in categories])\n",
    "\n",
    "# 在每个柱子顶部添加气泡式数值标签\n",
    "for i, (category, count) in enumerate(zip(categories, counts)):\n",
    "    # 获取柱子颜色\n",
    "    bar_color = colors_map[category]\n",
    "    \n",
    "    # 创建气泡式标签 - 圆角矩形带小尖角\n",
    "    bubble_width = 0.5\n",
    "    bubble_height = max(counts) * 0.04\n",
    "    bubble_bottom = count + max(counts) * 0.01\n",
    "    \n",
    "    # 主体气泡（圆角矩形）\n",
    "    bubble = FancyBboxPatch(\n",
    "        (i - bubble_width/2, bubble_bottom),  # (x, y) 左下角坐标\n",
    "        bubble_width,                          # 宽度\n",
    "        bubble_height,                         # 高度\n",
    "        boxstyle=\"round,pad=0.1,rounding_size=0.15\",  # 圆角设置\n",
    "        facecolor=bar_color,                   # 与柱子颜色一致\n",
    "        edgecolor='white',                     # 白色边框\n",
    "        linewidth=1.5\n",
    "    )\n",
    "    ax.add_patch(bubble)\n",
    "    \n",
    "    # 添加小尖角（三角形）\n",
    "    triangle_points = np.array([\n",
    "        [i, bubble_bottom],                    # 顶点（尖角底部）\n",
    "        [i - 0.08, bubble_bottom - 0.02],     # 左下角\n",
    "        [i + 0.08, bubble_bottom - 0.02]      # 右下角\n",
    "    ])\n",
    "    triangle = plt.Polygon(triangle_points, \n",
    "                          facecolor=bar_color,   # 与柱子颜色一致\n",
    "                          edgecolor='white',\n",
    "                          linewidth=1.5)\n",
    "    ax.add_patch(triangle)\n",
    "    \n",
    "    # 在气泡中添加数值文本\n",
    "    ax.text(i, bubble_bottom + bubble_height/2, str(count),\n",
    "            ha='center', va='center', fontsize=11, color='white', fontweight='bold')\n",
    "\n",
    "# 设置坐标轴\n",
    "ax.set_xlim(-0.8, len(categories)-0.2)\n",
    "ax.set_ylim(0, max(counts) * 1.15)\n",
    "\n",
    "# 设置Y轴刻度\n",
    "y_max = max(counts) + 20\n",
    "y_step = y_max // 5 if y_max // 5 > 0 else 10\n",
    "y_ticks = np.arange(0, y_max + y_step, y_step)\n",
    "ax.set_yticks(y_ticks)\n",
    "ax.set_yticklabels([str(int(tick)) for tick in y_ticks], color='white', fontsize=10)\n",
    "\n",
    "# 设置X轴刻度\n",
    "ax.set_xticks(x_pos)\n",
    "ax.set_xticklabels(categories, color='white', fontsize=12, fontweight='bold')\n",
    "\n",
    "# 设置坐标轴标签\n",
    "ax.set_ylabel('订单数量', color='white', fontsize=14, fontweight='bold', labelpad=20)\n",
    "ax.set_xlabel('产品类别', color='white', fontsize=14, fontweight='bold', labelpad=20)\n",
    "\n",
    "# 隐藏边框\n",
    "for spine in ax.spines.values():\n",
    "    spine.set_visible(False)\n",
    "\n",
    "# 隐藏网格线\n",
    "ax.grid(False)\n",
    "\n",
    "# 添加主标题\n",
    "plt.suptitle('3月商品销量对比', color='white', fontsize=22, fontweight='bold', y=0.95)\n",
    "\n",
    "# 添加副标题（位置降低）\n",
    "max_ratio = round(max_count / min_count, 1)\n",
    "plt.figtext(0.5, 0.90, f'{max_category}订单最多达{max_count}，是{min_category}最低值{min_count}近{max_ratio}倍', \n",
    "            ha='center', color='white', fontsize=14)\n",
    "\n",
    "# 添加数据来源说明\n",
    "ax.text(0.5, -0.12, '*注：数据来源于公司ERP系统，统计日期截至2024.03.31', \n",
    "        transform=ax.transAxes, ha='center', va='top', \n",
    "        color='lightgray', fontsize=11, alpha=0.8)\n",
    "\n",
    "# 调整布局\n",
    "plt.tight_layout()\n",
    "\n",
    "\n",
    "\n",
    "# 显示图形\n",
    "plt.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6511e12-66d1-484a-a13a-b48dc579ea72",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "20264976-b957-42aa-b8ed-88b602a52cb8",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
